Systems and methods for performing three-dimensional semantic parsing of indoor spaces

1. A method for parsing three-dimensional indoor spaces, the method comprising:

receiving input data representing a three-dimensional indoor space;

determining disjointed spaces within the received input data by:

generating a density histogram on each of a plurality of axes of the three-dimensional indoor space;

determining space dividers based on the generated density histogram by:

locating a void space enclosed by a histogram signal peak on either side of the void space; and

convolving the density histogram with a series of filters in a filter bank;

dividing the input data into segments based on the determined space dividers; and

determining structural elements in the disjointed spaces by:

aligning the disjointed spaces within the input data along similar axes to create aligned versions of the disjointed spaces;

normalizing the aligned version of the disjointed spaces into a unit cube;

determining features in the unit cube;

generating at least one detection score based on the determined features representing the probability of the presence of an element; and

filtering the at least one detection score to determine a final set of determined elements.

2. The method of claim 1 , wherein the input data received can be from multiple sources.

3. The method of claim 2 , wherein the multiple sources of input data are correlated to each other by at least one reference point, creating a registered set of data.

4. The method of claim 2 , wherein the multiple sources of input data is selected from the group of: point cloud data, three-dimensional meshes, three-dimensional surface normals, depth images, RGB images, and RGB-D images.

5. The method of claim 1 , wherein determining disjointed spaces within input data further includes:

generating a graph of all neighboring segments;

evaluating each neighboring segment for a space divider between the neighboring segments;

removing edges from the graph when a space divider is detected;

creating connected components between all neighboring segments with edges remaining; and

merging connected component segments into disjointed spaces.

6. The method of claim 1 , wherein the received input data represents the interior of an entire building.

7. The method of claim 1 , wherein determining structural elements in the disjointed spaces further includes assigning determined structural elements to a class.

8. The method of claim 7 , wherein determining structural elements in the disjointed spaces further includes reevaluation of the determined structural elements by:

generating a graph of all neighboring disjointed spaces;

evaluating each neighboring disjointed space for a detected wall class between neighboring disjointed spaces;

removing edges from the graph when a space divider is detected;

creating connected components between all neighbors with edges remaining; and

merging connected component disjointed spaces.

9. A semantic parsing system comprising:

a processor;

at least one input;

a memory connected to the processor, where the memory contains;

a parsing application;

wherein the parsing application directs the processor to:

receive input data representing a three-dimensional space;

determine disjointed spaces within the received input data, where:

a density histogram on each of a plurality of axes of the three-dimensional indoor space is generated;

space dividers based on the generated density histogram are determined, where to generate the space dividers, a void space enclosed by a histogram signal peak on either side of the void space is located; and

the density histogram is convolved with a series of filters in a filter bank; and

the input data is divided into segments based on the determined space dividers; and

determine structural elements in the disjointed spaces, where:

the disjointed spaces within the input data are aligned along similar axes;

the disjointed spaces within the input data are normalized into unit cubes;

features in the unit cubes are detected;

at least one detection score is generated based on the detected features representing the probability of the presence of an element; and

the at least one detection score is filtered to determine a final set of determined elements.

10. The semantic parsing system of claim 9 , wherein the input data received can be from multiple sources.

11. The semantic parsing system of claim 10 , wherein the multiple sources of input data can be correlated to each other by at least one reference point, creating a registered set of data.

12. The semantic parsing system of claim 10 , wherein the multiple sources of input data is selected from the group of: point cloud data, three-dimensional meshes, three-dimensional surface normals, depth images, RGB images, and RGB-D images.

13. The semantic parsing system of claim 9 , wherein determining disjointed spaces within input data further includes:

generating a graph of all neighboring segments;

evaluating each neighboring segment for a space divider between the neighboring segments;

removing edges from the graph when a space divider is detected;

creating connected components between all neighboring segments with edges remaining; and

merging connected component segments into disjointed spaces.

14. The semantic parsing system of claim 9 , wherein the received input data represents the interior of an entire building.

15. The semantic parsing system of claim 9 , wherein determining structural elements in the disjointed spaces further includes assigning determined structural elements to a class.

16. The semantic parsing system of claim 9 , wherein determining structural elements in the disjointed spaces further includes reevaluation of the determined structural elements by:

generating a graph of all neighboring disjointed spaces;

evaluating each neighboring disjointed space for a detected wall between neighboring disjointed spaces;

removing edges from the graph when a space divider is detected;

creating connected components between all neighbors with edges remaining; and

merging connected component disjointed spaces.